Script 915: Bidding Strategy Assignment

Purpose:

The Python script automatically assigns a campaign to a specific bidding strategy based on the campaign’s age.

To Elaborate

The script is designed to manage the assignment of bidding strategies to advertising campaigns based on their creation date. Specifically, it assigns a campaign to an “Impression Share Strategy” called ‘Data Gathering’ if the campaign is less than or equal to 7 days old. If the campaign has been active for more than 7 days, it is switched to a “CPA strategy” called ‘Performance Bidding’. This transition is marked by updating the ‘Folder Check’ column to “YES” for campaigns older than 7 days, while leaving it blank for newer campaigns. This automated process helps streamline the management of campaign strategies by ensuring that new campaigns start with data gathering before moving to performance-focused bidding.

Walking Through the Code

  1. Data Preparation
    • The script begins by copying the input DataFrame to ensure the original data remains unchanged.
    • It converts the ‘Campaign Creation Date’ column from string format to datetime objects to facilitate date comparisons.
  2. Strategy Assignment Logic
    • The script iterates over each row in the DataFrame to evaluate the age of each campaign.
    • If a campaign’s creation date is within 7 days of the current date, it assigns the ‘Data Gathering’ strategy and leaves the ‘Folder Check’ column blank.
    • For campaigns older than 7 days, it assigns the ‘Performance Bidding’ strategy and sets the ‘Folder Check’ column to “YES”.
  3. Output
    • The modified DataFrame is printed to show the changes in strategy and folder check status for each campaign.
    • The processed DataFrame is returned for further use or analysis.

Vitals

  • Script ID : 915
  • Client ID / Customer ID: 1306926015 / 69058
  • Action Type: Bulk Upload
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Strategy, Folder Check
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Jeremy Brown (jbrown@marinsoftware.com)
  • Created by Jeremy Brown on 2024-04-11 09:01
  • Last Updated by Jeremy Brown on 2024-04-11 09:01
> See it in Action

Python Code

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##
## name: Bidding Strategy Assignment
## description:
##
## The Script automatically assigns a campaign to an Impression Share Strategy called 'Data Gathering' for the first 7 days after being created. Then after the campaign has been live for 7 days it is moved to a CPA strategy called 'Performance Bidding'. The logic is as follows;
## When a campaign's creation date is within 7 days of today's date, it is assigned to "Data Gathering" with a blank Folder Check column (""). Otherwise, it's assigned to "Performance Bidding" with a "YES" in the Folder Check column.
## 
## author: Jeremy Brown
## created: 2024-04-11
## 

today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_STRATEGY = 'Strategy'
RPT_COL_CAMPAIGN_CREATION_DATE = 'Campaign Creation Date'
RPT_COL_FOLDER_CHECK = 'Folder Check'
RPT_COL_IMPR = 'Impr.'

def process(inputDf):
    # Make a copy of the input DataFrame
    outputDf = inputDf.copy()
    
    # Get today's date in the specified timezone
    today_date = datetime.datetime.now(CLIENT_TIMEZONE).date()
    
    # Convert 'Campaign Creation Date' column to datetime objects (assuming format dd/mm/yyyy)
    outputDf['Campaign Creation Date'] = pd.to_datetime(outputDf['Campaign Creation Date'], format='%d/%m/%Y')
    
    # Determine the strategy and folder check based on the campaign creation date
    for index, row in outputDf.iterrows():
        creation_date = row['Campaign Creation Date'].date()
        if (today_date - creation_date).days <= 7:
            # Within 7 days of today's date
            outputDf.at[index, 'Strategy'] = "Data Gathering"
            outputDf.at[index, 'Folder Check'] = ""  # Leave Folder Check blank
        else:
            # More than 7 days old
            outputDf.at[index, 'Strategy'] = "Performance Bidding"
            outputDf.at[index, 'Folder Check'] = "YES"
    
    # Debugging: Print changes made to outputDf
    print("Data Changed:")
    print(outputDf[['Account', 'Campaign', 'Strategy', 'Folder Check']])
    
    return outputDf

# Example usage:
# Assuming inputDf is your actual DataFrame with the appropriate columns
# inputDf = ...

# Process the DataFrame
outputDf = process(inputDf)

Post generated on 2025-03-11 01:25:51 GMT

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